A stochastic method for convective storm identification, tracking and nowcasting |
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Authors: | Lei Han Shengxue Fu Guang Yang Hongqing Wang Yongguang Zheng Yingjing Lin |
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Affiliation: | 1. College of Information Science and Engineering, Ocean University of China, Qingdao 266101, China;Department of Atmospheric Science, Peking University, Beijing 100871, China 2. College of Information Science and Engineering, Ocean University of China, Qingdao 266101, China 3. Department of Probability and Statistics, Peking University, Beijing 100871, China 4. Department of Atmospheric Science, Peking University, Beijing 100871, China 5. National Meteorological Center, Beijing 100081, China |
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Abstract: | The convective storm identification, tracking and nowcasting method is one of the important nowcasting methodologies against severe convective weather. The new generation weather radar network is under construction in China which will greatly benefit the severe weather warning operations. In severe convective cases, such as storm shape or velocity changes rapidly, existing methods are apt to provide unsatisfied storm identification, tracking and nowcasting results. To overcome these difficulties, this paper proposes a novel approach to identify, track and short-term forecast (nowcast) convective storms. A mathematical morphology-based storm identification method is adopted which can identify storm cells accurately in a cluster of storms. As for the difficult tracking problem, sequential Monte Carlo (SMC) method is utilized to simplify the tracking process. It is not only inherently suitable for handling complicated splits and mergers, but also capable of handling the case of storm missing detection. In order to provide more accurate forecast of a storm position, this method takes the advantages of the cross correlation method. The qualitative and quantitative evaluations show the efficiency and robustness of the proposed approach. |
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Keywords: | Convective storm Doppler radar Nowcasting |
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